Multivariate analysis | Univariate analysis | ||||||||
---|---|---|---|---|---|---|---|---|---|

Term | Pillai statistic | F(3,137) (P) | η^{2} | ADI-R, scale A | ADI-R, scale B | ADI-R, scale C | |||

F(1,139) (P) | η^{2} | F(1,139) (P) | η^{2} | F(1,139) (P) | η^{2} | ||||

Gender | 0.07 | 3.4 (0.019) | 0.07 | 5.7 (0.018) | 0.04 | 9.0 (0.003) | 0.06 | 4.9 (0.029) | 0.03 |

Age | 0.05 | 2.2 (0.090) | 0.05 | 5.2 (0.024) | 0.04 | 1.3 (0.253) | 0.01 | 2.4 (0.126) | 0.02 |

Verbal IQ | 0.10 | 4.9 (0.003) | 0.11 | 6.8 (0.01) | 0.05 | 15.0 (<0.001) | 0.10 | 2.1 (0.150) | 0.01 |

Group | 0.07 | 3.2 (0.025) | 0.06 | 3.3 (0.070) | 0.02 | 4.0 (0.046) | 0.03 | 8.7 (0.004) 0.06 |

↵a. Univariate analysis are all based on type III sums of squares. Partial eta-squared (η

^{2}) is a measure of effect size (small: 0.01; medium: 0.09; large: 0.25; based on the square of the Pearson correlation effect sizes from Cohen^{19}). Multivariate η^{2}= 1 – Λ^{1/s}where Λ = Wilks' lambda and s = minimum of the number of levels of the factor minus 1, or the number of dependent variables (here, s = 1 for continuous variables).^{20}